Shi-Lung Shaw, professor of geography, will receive an award for his paper A Sensor-Fusion Drivable-Region and Lane-Detection System for Autonomous Vehicle Navigation in Challenging Road Scenarios, originally published in IEEE Transactions on Vehicular Technology in 2014.
The IEEE Vehicular Technology Society Awards Committee will honor Shaw and his team with the 2018 Best Land Transportation Paper Award, which recognizes the best propagation paper published in IEEE Transactions on Vehicular Technology in the past 5 years. The award will be presented to his Shaw and research collaborators on August 29, at the Fall 2018 Vehicular Technology Conference in Chicago.
A Sensor-Fusion Drivable-Region and Lane-Detection System for Autonomous Vehicle Navigation in Challenging Road Scenarios demonstrates a novel real-time optimal-drivable region and lane detection system for autonomous driving, based on both the fusion of light detection and ranging (LIDAR) and vision data. Multiple sensors cover the most drivable areas in front of an autonomous vehicle, and then a conditional lane detection algorithm selects optimal route. Shih-Lung and research collaborators demonstrate the effectiveness of this system on both structured and unstructured roads, a challenge autonomous vehicles face in real urban environments.
Raphael Rosalin (865-974-2152, email@example.com)